Partially Observable Stochastic Optimal Control

Partially Observable Stochastic Optimal Control

Year:    2016

International Journal of Numerical Analysis and Modeling, Vol. 13 (2016), Iss. 4 : pp. 493–512

Abstract

This paper is a survey on some recent results in optimal control and stochastic filtering. The goal is not to cover all recent developments in control and filtering, instead we focus on maximum principle for optimality of partial information backward or forward-backward stochastic differential equations and branching particle approximation of nonlinear filtering.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/2016-IJNAM-449

International Journal of Numerical Analysis and Modeling, Vol. 13 (2016), Iss. 4 : pp. 493–512

Published online:    2016-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    20

Keywords:    Branching particle system forward-backward stochastic differential equation numerical approximation maximum principle stochastic filtering.